ArticleFrontiers in microbiology2026
Metagenomic insights into microbial diversity, xenobiotic and plastic-degrading enzymes in sediments of river Yamuna at Agra.
Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The river Yamuna is one of the most polluted rivers in India and is heavily impacted by urban, industrial, and agricultural inputs. In this study, shotgun metagenomics was used to investigate microbial diversity and functional potential in sediments from three locations: Balkeshwar Shivpuri Agra (BSA), Taj Ganj Yamuna (TGY), and Yamuna Expressway Agra (YEA). A total of 38.3-46.5 million reads per sample were generated, yielding 3.08-5.54 million predicted ORFs. Taxonomic profiling revealed that BSA exhibited higher microbial diversity, with a more even distribution of dominant taxa compared to TGY and YEA. Functional analysis indicated that core metabolic pathways (e.g., glycolysis and TCA cycle) were more abundant in BSA, whereas pathways related to aromatic compound degradation were relatively enriched in TGY. Plastic-degrading enzyme homologs were detected across all sites, with the strongest signals associated with biodegradable polymers such as polyhydroxyalkanoates (PHA), polyhydroxybutyrate (PHB), and polyethylene glycol (PEG). The normalized abundances of PHA-associated enzymes were approximately 60-75% higher in YEA compared to BSA and TGY, while homologs linked to recalcitrant plastics such as polyethylene (PE) and low-density polyethylene (LDPE) were detected at low levels across all sites (< 10-15%). Similarly, xenobiotic degradation pathways, including chlorocyclohexane and chlorobenzene degradation, showed relatively higher abundance in YEA, whereas bisphenol degradation was more prominent in BSA. Overall, the results indicate that sediment microbial communities along the river Yamuna harbor diverse metabolic capabilities and functional potential for pollutant degradation, with site-specific variations driven by local environmental conditions.
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